Brain function is dictated by its circuitry, yet we know little about its wiring architecture: in the most-studied mammal (rat), only an estimated 10-30% of the long range circuit connections have been probed. There is growing consensus that it is time to close this gap by generating brainwide connectivity maps for model vertebrates. The mouse is the starting species of choice: mouse models form the backbone of research into the etiology of neuropsychiatric disorders, have the most-studied genome of any mammal, and are key to the early stages of drug development. Over the last two years, we have organized several meetings involving the neuroanatomy community to gain in-depth understanding of the technical and scientific challenges of such a project. Based on this experience, we propose to produce the first brainwide connectivity map of mouse, through the development of an automated pipeline of experimental and computational techniques-- a connectivity scanner. Our proposal is timely and is enabled by advances in automated wide-field slide scanning microscopy, decreasing data-storage costs, and established tract-tracing methods using injections of classical tracers and neurotropic viruses. The need for brain-wide scope and scalability rule out other approaches. To demonstrate the translational utility of the approach, we will also analyze disease model mice (autism and schizophrenia), to understand alterations in the connectivity map compared to the reference map generated in the project. The project does not fit neatly into an existing funding mechanism at the NIH, but has the potential to fundamentally impact the entire neuroscience community. The transformative potential is twofold: by generating the first mammalian brainwide connectivity map, we provide the neuroscientific community with a landmark reference map which can be used in a wide variety of contexts. Secondly, our emphasis on open source software development, cost optimization and duplicability will result in an affordable, integrated instrument which other academic laboratories will be able to implement. In this way it borrows from, yet differs significantly from, the model offered by the Allen Institute, which has previously demonstrated the potential of industrial automation for neuroscience.